## Visual Abstract

## Abstract

**Background and objectives** To evaluate the growth pattern of kidney cyst number and cyst volume in association with kidney size, demographics, and genotypes in autosomal dominant polycystic kidney disease.

**Design, setting, participants, & measurements** Kidney cyst number and cyst volume were measured from serial magnetic resonance images, giving a maximum follow-up of 14.23 years, from 241 patients with autosomal dominant polycystic kidney disease (15–46 years old at baseline). The growth pattern was analyzed, in association with sex, age, height-adjusted total kidney volume, and genotype, using linear mixed models of repeated measurements and tests of interactions with age (as a time-dependent covariate) to assess rates of change over time. Models were also fit using Irazabal class. Genotypic groups were characterized as either (*1*) *PKD1* truncating, *PKD1* nontruncating, and *PKD2* plus patients with no mutation detected; or (*2*) in combination with *PKD1* mutation strength groups.

**Results** Imaging and genetic data were collected (at least one visit) for 236 participants. The mean height-adjusted total cyst number increased exponentially over time from a baseline value of 762 to 1715 at the last clinic visit, while the mean height-adjusted total cyst volume increased exponentially from 305 to 770 ml. Height-adjusted total kidney volume, height-adjusted total cyst number, and height-adjusted total cyst volume were all highly correlated over time. Female participants and participants with larger height-adjusted total kidney volume at baseline showed smaller rates of change in the log of height-adjusted total cyst number and cyst volume. *PKD1* was associated with significant increases in both cyst number and volume at a given age, but genotype did not significantly affect the rate of growth.

**Conclusions** Both height-adjusted total cyst number and height-adjusted total cyst volume increased exponentially and more than doubled over 14.23 years of follow-up. Compared with *PKD2* plus no mutation detected, *PKD1* was associated with a greater cyst number and volume at a given age, but no significant difference in the rate of growth.

- ADPKD
- cystic kidney
- kidney volume
- Polycystic Kidney, Autosomal Dominant
- Follow-Up Studies
- Cysts
- kidney
- Genotype
- Mutation
- Demography
- Ambulatory Care

## Introduction

The hallmarks of autosomal dominant polycystic kidney disease (ADPKD) are the progressive development and expansion of kidney cysts, causing life-altering symptoms and potentially lethal complications (1). The cysts, developing initially from relatively few kidney tubules, continue to grow and expand over time. In many cases, the cysts compress normally functioning kidney parenchyma and progressively impair kidney function.

The progression of ADPKD is complex and multifactorial. ADPKD is caused predominantly by mutations in two genes, *PKD1* (16p13.3) and *PKD2* (4q21), that encode the proteins polycystin-1 and polycystin-2 (2,3). Most patients (approximately 80%–85%) have PKD1, with PKD2 accounting for the remainder (4–6). Compared with PKD1, PKD2 is consistently a milder disease as evidenced by age at ESKD, diagnosis, and onset of hypertension (6–8). However, genetic modifying factors plus environmental factors significantly influence the course of ADPKD (9,10).

To expand our understanding of ADPKD disease progression, the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) was established. A longitudinal cohort of patients with ADPKD in the early course of their disease at baseline was followed by serial magnetic resonance imaging (MRI), kidney functional parameters, and other markers of disease progression (11). The CRISP study documented that total kidney volume measurements from MRI are more sensitive than kidney function measures in assessing yearly progression of early disease, and that the growth in kidney volume directly stems from increases in kidney cyst volume (12).

In addition to total kidney volume and cyst volumes, the progression of cyst number in each kidney also provides important information about the characteristics and progression of ADPKD. For example, differences in kidney morphology between PKD1 and PKD2 are likely due to the number of kidney cysts rather than faster volumetric growth of cysts in PKD1 kidneys (13). Although the progression of total kidney volume in ADPKD is well established and published extensively, the growth pattern of kidney cyst number and volume has rarely been reported. This paucity of research, is, in part, because the measurement of kidney cyst number and cyst volume is much more laborious than the measurement of total kidney volume, in general involving time-consuming and labor-intensive counting of cysts and measurement of cyst areas on MRI slices.

We postulate that the growth pattern of kidney cyst number and volume in ADPKD provides additional information to characterize the progression of disease. Here, we have generated unique longitudinal data, including repeated measurements of kidney cyst number and volume data from the CRISP study, to explore the nature and magnitude of the relationship between total kidney volume, demographics, and PKD genotype with progression in kidney cyst number and volume.

## Materials and Methods

The study protocol for the CRISP and the baseline characteristics of the cohort have been described in previous publications (11,12,14). The study was approved by the institutional review board at each participating clinical center, and informed consent was obtained from all study participants.

### Participants and MRI

In the CRISP study, which was launched in 1999 to acquire prospective, multiyear, longitudinal clinical and imaging data in a large cohort of participants with ADPKD, 241 patients with ADPKD between 15 and 46 years old with relatively intact kidney function were recruited. As part of the CRISP study protocol, standardized MRI images were obtained at four clinical centers (Mayo Clinic, Emory University, University of Kansas Medical Center, and University of Alabama at Birmingham). From the baseline visit, a total of up to 12 visits were conducted over 14.23 years. At each visit, magnetic resonance images of kidneys were acquired at 3 mm fixed slice thickness in the coronal plane, using both three-dimensional spoiled gradient interpolated T1-weighted without fat saturation and single-shot fast spin-echo T2-weighted with fat saturation sequences (11).

### Measurement of the Number of Kidney Cysts

Manual counting of every kidney cyst from the entire magnetic resonance images is tremendously laborious, particularly in kidneys of severe cyst burden with numerous cysts. Therefore, cysts were counted in three selected sample slices of each magnetic resonance image set. From a series of coronal T2-weighted magnetic resonance images of the right or left kidney in each participant, we selected the midslice by reviewing and scrolling the image set. We defined the midslice as the slice whose image number corresponded to a half of the sum of the first slice and last slice image numbers in the image set (if the sum was odd, the midslice corresponded to the neighboring slice, rounding up from the mean). In addition to the midslice (*i.e.*, the second quartile) image, we also selected two additional slices from each kidney image series: the midslice of the anterior half (the first quartile) and the midslice of the posterior half (the third quartile) of the series.

The number of cysts from the three slices in each kidney was counted manually by a radiologist. Only circular and spheroid structures ≥2 mm in diameter whose signal intensities were close to that of spinal fluid were considered cysts (Figure 1). Each identified and counted cyst was flagged by an electronic marker using an in-house cyst-labeling program. The number of cysts flagged with red marks was automatically calculated. The number of cysts counted from the three slices were divided by three to represent the number of cysts at one-slice equivalent from each magnetic resonance image dataset. The total cyst number in each kidney from the magnetic resonance image dataset was approximated using the following formula: total cyst number=average slice cyst number×total slice number×2/3. The coefficient 2/3 is on the basis of the approximation of the shape of kidney as an ellipsoid and was shown to be reasonable for approximating total kidney and cyst volume from midslice measurement in a previous study (15).

### Cyst Area Measurements Using Region-Based Method

The total volume of cysts in each kidney was measured using a region-based thresholding method on T2-weighted magnetic resonance images (11,14). Cysts that were brighter than the kidney parenchyma could be measured by summing pixels with intensity values greater than those of the background kidney parenchyma. On each kidney magnetic resonance image slice, a binary signal-intensity map was generated by determining a threshold signal intensity that visually distinguished the cyst and kidney parenchymal regions. By summing the pixels of white regions in the binary map, the cystic area was measured in every slice. The total cyst volume was calculated from each set of contiguous images by summing the products of the areas measured and the slice thickness.

### Statistical Analyses

#### Descriptive Statistics.

Continuous variables, including height-adjusted total cyst number and height-adjusted total cyst volume, height-adjusted total kidney volume, and age were described using the mean, SD, and range (minimum, maximum). Frequencies and percentages were calculated for categories of sex and genotype. Genotype was grouped as *PKD1* truncating, *PKD1* nontruncating, and *PKD2* plus patients with no mutation detected. Furthermore (as a secondary analysis), to evaluate the associations with PKD gene mutation strength groups (MSGs), the genotype and MSGs were grouped as (*1*) *PKD1*, MSG1+MSG2; (*2*) *PKD1*, MSG3; or (*3*) *PKD2* plus patients with no mutation detected, as reported in a recent study (16). To investigate the correlation among the height-adjusted total kidney volume, height-adjusted total cyst volume, and height-adjusted total cyst number, Pearson correlation coefficients were calculated by visit. Histograms and q-q plots were used to show the distribution of these variables. Visits are labeled as 0 through 12. During the first 5 years after baseline (*i.e.*, visit 0), the numbers for each visit correspond to the number of years after baseline. After the 5 years, those visits continued over a year or two (with the last clinic visit, visit 12, being measured as late as 14.23 years after baseline).

#### Repeated Measures Analysis of Cyst Number or Volume.

This analysis uses a linear mixed model (with a random intercept and random slope to account for within-subject correlation and individual differences) to assess relationships between genotype and natural log-transformed cyst numbers (or volumes) measured over time. This model adjusts for sex and baseline log height-adjusted total kidney volume (or with Irazabal class [17], which categorizes the estimated rate of increase in height-adjusted total kidney volume from age and a single height-adjusted total kidney volume measurement) and a time-dependent variable for patient age (at the time of the imaging measurements). The coefficients and *P* values for genotype (or sex or baseline height-adjusted total kidney volume) in this model thus assess the effect of genotype (other sex or baseline height-adjusted total kidney volume, holding the other factors constant) on the expected cyst number or volume at a given age. The interpretation of age, however (as a time-dependent covariate), is the effect of a 1-year increase in age on the cyst number or volume within a given participant.

#### Modeling the Rate of Change in Cyst Number or Volume.

In contrast to the first analysis, which assesses relationships between genotype and cyst numbers (or volumes) at a given age, this subsequent “slope analysis” assesses whether genotype (adjusted for baseline factors) is associated with the rate of change in cyst number or cyst volume. More specifically, the interaction between age (as a time-dependent covariate) and genotype were added to the above-described linear mixed models. The age-genotype interaction characterizes the differences in individual’s rate of change (in a log scale) over time between genotypes. Relationships between those slopes and genotype were then assessed using likelihood ratio test adjusted for sex, and baseline height-adjusted total kidney volume (or Irazabal class). Tests of interactions were also conducted in the same manner for sex by age interaction and baseline height-adjusted kidney volume by age interaction.

All tests were done with a two-sided significance level of 0.05, and Stata version 14 (18) was used for all statistical analyses.

## Results

### Descriptive Analysis

Out of 241 CRISP participants, 236 who had genotype records were included in the analysis. The baseline characteristics of the study cohort of 236 participants is shown in Table 1. At baseline, there were 95 males and 141 females (mean age, 32 years; SD 9 years; range 15–46 years). The median baseline height-adjusted total kidney volume was 503 ml (interquartile range, 350–757 ml/m). The primary categorization for genotype was *PKD1* truncating (*n*=126), *PKD1* nontruncating (*n*=62), and *PKD2* or no mutation detected (*n*=31 or *n*=17, respectively). For the secondary analysis on the basis of MSGs (16), genotype was categorized as *PKD1*, MSG1 or MSG2 (*n*=165); *PKD1*, MSG3 (*n*=23); and *PKD2* or no mutation detected (*n*=48). Overall, both cyst number and volume more than doubled over 14.23 years of follow-up. The trajectories of individual cyst number and cyst volume (both height-adjusted in the log scale) plotted against the participants’ age at visit was approximately linear on the log scale (Figure 2), indicating that cyst number and volume increase exponentially over time.

The cohort had an average visit number of 6.1 times during 14.23 years of follow up. The characteristics of the cohort compared between the baseline and visits is summarized in Supplemental Table 1. The mean height-adjusted total cyst number increased over time from a baseline value of 762 (SD 525) to 1715 (SD 965) at the last clinic visit (Supplemental Table 2A). The mean height-adjusted total cyst volume also more than doubled across the study period (Supplemental Table 3A) from a baseline value of 305 ml (SD 298) to 770 ml (SD 646) at the last clinic visit. Reasons for missing visits included (*1*) reaching the end point of either death (*n*=3; 1.2%) or ESKD (*n*=47; 19.5% on dialysis, receiving a transplant, and/or reaching stage 5 CKD), (*2*) withdrawing from the study (*n*=9; 3.7%), and (*3*) inability to reach participants (who were originally consented before 2000) or inability of participants to come in for visits (*e.g.*, because of work or family demands). Furthermore, to address the potential concern of participation bias (from healthier participants remaining in the study longer), the height-adjusted total cyst number and volume over time analysis was repeated in the subset of participants with at least one visit in each 5-year period (*i.e.*, 0–5, 6–10, and over 10 years after baseline; see Supplemental Tables 2B and 3B); that analysis showed very similar results.

### Correlation Analysis: Height-Adjusted Total Kidney Volume, Total Cyst Volume, and Total Cyst Number

In ADPKD, total kidney volume increases over time because of increasing total cyst volume, which is likely, in part, because of an increase in cyst number. Height-adjusted total kidney volume, total cyst volume, and total cyst number data that were right-skewed distributed, were normally distributed after log transformation (Supplemental Figure 1). Table 2 confirms that there were strong correlations between height-adjusted total kidney volume and height-adjusted total cyst volume (correlation coefficients range 0.93–0.97). The correlation coefficients ranged from 0.78 to 0.86 between height-adjusted total kidney volume and total cyst number, and from 0.83 to 0.90 between height-adjusted total cyst volume and total cyst number.

### Repeated Measures Analysis: Height-Adjusted Total Cyst Number and Volume (Linear Mixed Model)

The height-adjusted total cyst number and height-adjusted total cyst volume are predicted to increase annually by 7.3% and 10.3%, respectively (Tables 3 and 4). Both PKD1 nontruncating and truncating had significantly higher height-adjusted total cyst number (1.77-fold and 2.31-fold, respectively; Table 3) relative to PKD2 or no mutation detected, as did participants with larger baseline height-adjusted total kidney volume (*P*<0.001 for each test), but sex was not significantly related to height-adjusted total cyst number (*P*=0.88). Median height-adjusted total cyst number and total cyst number breakdowns by the age group at baseline and genotype are summarized in Supplemental Table 4, A and B. Similarly, height-adjusted total cyst volume (Table 4) was also greater for PKD1 truncating (by 2.0-fold; 95% confidence interval, 1.5 to 2.7; on the basis of exponentiating the coefficient and confidence intervals in the mixed model; *P*<0.001) and nontruncating (1.5-fold; 95% confidence interval, 1.1 to 2.1; *P*=0.02) versus PKD2 or no mutation detected, and for larger baseline height-adjusted total kidney volume (*P*<0.001). Sex was not significantly related to height-adjusted total cyst volume (*P*=0.13). Trajectories of the mean log height-adjusted total cyst number and volume at each genotype group indicated that the height-adjusted total cyst number and volume increases exponentially over time (Figure 3). The linear mixed models were then used to predict height-adjusted total cyst number and volume (both in the log scale) over study visits, stratified by genotype, and adjusted for sex, age at visit, and baseline height-adjusted total kidney volume (Figure 4). The predicted trajectories for cyst number and volume follow the same pattern as the mean observed trajectories. The results from the secondary analysis for the MSG genotype and Irazabal class categorization are shown in Supplemental Tables 5, A and B and 6, A and B, respectively. The associations between the factors were very similar to those from the primary genotype categorization.

### Rates of Change Analysis: Height-Adjusted Total Cyst Number and Volume

There was no significant difference in the rate of change of log height-adjusted total cyst number between the different genotypes (*P*=0.24); both coefficients for the two PKD1 mutation interactions were near 0, suggesting that the difference of slopes between two *PKD1* mutation groups and *PKD2* plus no mutation detected was negligible (Table 5, model 1). However, female sex (*P*<0.001) and higher baseline log height-adjusted total kidney volume (*P*<0.001) were both negatively associated with the rate of change of log height-adjusted total cyst number (Table 5, models 2 and 3). Females were estimated to have 0.02 lower growth rate in log height-adjusted total kidney number compared with males, adjusting for genotype and baseline kidney volume; one-unit increase in baseline log height-adjusted total kidney volume would lead to a 0.01 decrease in the growth rate of log height adjusted total cyst number, controlling for genotype and sex. Analysis of slopes in log of height-adjusted total cyst volume showed a similar relationship (Table 6). Cyst volume growth rate were not significantly different among three genotypes (*P*=0.31). Both female sex (*P*<0.001) and higher baseline log height-adjusted total kidney volume (*P*=0.003) were associated with slower increase (smaller slope) of log height-adjusted total cyst volume. The models for genotype on the basis of MSG (Supplemental Table 7, A and B) and Irazabal class (Supplemental Table 8, A and B) showed very similar results.

## Discussion

Compared with our previous publication (13), the scope of this study was expanded including more rigorous estimate of cyst number (three slices versus a single slice), longer follow-up (14.23 versus 3 years), and more detailed analysis of PKD1 genotype (truncating versus nontruncating and MSG). In addition, we investigated the growth pattern of ADPKD kidney cyst number and volume and associations with sex, genotype, baseline height-adjusted total kidney volume, and age using linear regression analysis of slopes (to capture the rate of change) and linear mixed models of repeated measures over time. Overall, both height-adjusted total cyst number and cyst volume more than doubled over 14.23 years of follow-up, with height-adjusted total cyst volume, cyst number, and kidney volume being highly correlated. The increase in height-adjusted total cyst number and volume over time appeared exponential.

The inclusion criteria for CRISP (which enrolled participants from age 15–46 at baseline) required well preserved kidney function at the time of study recruitment in 1999 (to then study the natural history of disease). This inclusion criteria would then almost definitely exclude any older participants who were experiencing steep trajectories of cyst growth (and would thus also have poor kidney function and be ineligible for CRISP). In contrast, younger patients with the same trajectory of cyst growth and/or development would be less likely to have already reached a sufficiently low level of kidney function, thus introducing a selection bias in the association with age. This bias may explain the seemingly inconsistent result that the two oldest PKD1 truncating subgroups had smaller median height-adjusted total cyst number than the next younger subgroup, when the median height-adjusted total cyst number was broken down according to the baseline age group and genotype. The age-dependent growth pattern of rate of cyst development and height-adjusted total cyst volume increase could however also suggest that kidney cysts form early in the disease and that fewer new cysts develop in older individuals (13,19). Female sex was also associated with slower rates of cyst volume growth, consistent with the increasing evidence that ADPKD is a more severe disease in males (7,16,20–23).

The relationship between height-adjusted total cyst number and height-adjusted total cyst volume and genotype was complex. Cyst number and volume were significantly higher in PKD1 (both truncating and nontruncating) compared with PKD2 or no mutation detected at any given age, but there were no significant differences in the rate of change of cyst number or volume. The same trend was reported in a previous cross-sectional study evaluating differences in baseline cyst number and volume growth rate between PKD1 and PKD2 (13). If CRISP data could be extrapolated over the entire lifetime, this would imply that patients with PKD1 are born with more cysts than those with PKD2, but then grew at the same rate, *i.e.*, they have different intercepts but similar slopes. However, a more likely explanation is that there is a phase of rapid cyst development in PKD1 kidneys that occurs early in life, before the observed age range of our data.

The interpretation of model coefficients is also complicated by use of ln-transformations (which is needed to satisfy assumptions of the linear and linear mixed models). To provide some explanation of the coefficients, note that the difference between the first quartile and median ln-transformed cyst number varied between 0.39 and 0.56 (across all time points); similarly, the difference between the median and third quartile varied between 0.32 and 0.48 (using the summary statistics from Supplemental Table 2A). Therefore, the coefficients for genetic mutations PKD1 nontruncating or PKD1 truncating (0.57 and 0.84, respectively; see Table 3), are highly clinically meaningful. Similar conclusions can be made regarding the coefficients in Table 4 (using the summary statistics from Supplemental Table 3A).

Caution is warranted when interpreting the linear mixed models for subject-specific slopes in the log scale (and the associated lack of significance for genotype). If for instance, we consider two trajectories, that are linear in a log scale, with a different intercept but the same slope in the log scale, they will appear as parallel lines in the log scale. However, when transforming the data back to the original scale, the trajectories will be closer together at the initial *x*-value or time point (*e.g.*, age) and then separate further over time. The transformation to the log scale is required to meet assumptions of the linear mixed models, but also need to be considered in the subsequent interpretation.

The study has limitations. First, microscopic cysts in the kidney were not counted. For the measurement of cyst number, we only considered circular and spheroid structures ≥2 mm in diameter whose signal intensities were close to that of spinal fluid. As shown in a previous study (24), a vast number of microscopic cysts present in ADPKD kidneys remain undetected by clinically available imaging modalities, and the collective volume of these microscopic cysts is quantitatively insignificant compared with the overall cyst volume. Second, the total number of cysts in a kidney was computed on the basis of three sample slices in each magnetic resonance image dataset. Although it would be ideal to count all cysts from the entire magnetic resonance image slices, some large kidneys have 40–60 slices, requiring impractical amount of time and effort to count all cysts in every slice without automation of this process. On the basis of the previous study (15), we believe that the average counts from three sample slices multiplied by the number of slides of the magnetic resonance dataset provided a good approximation of the total cyst number, as evidenced by the high correlation coefficients between height-adjusted total cyst number, cyst volume, and kidney volume. Third, although we addressed the potential concern of participation bias in the analysis and found insignificant, the distribution of cohort participation between visits was uneven. For example, there was a slightly higher percentage of patients with *PKD2* or no mutation detected present in the cohort at visit 12 than earlier visits, which may relate to presence of milder disease in these individuals. Finally, the findings of the study were analyzed mainly on the basis of statistical correlations and model fitting. Biologic implication and causality of the findings is yet to be determined.

In conclusion, our longitudinal study of growth pattern of kidney cyst number and volume in ADPKD showed that both cyst number and volume increased exponentially over time, and nearly doubled over 14.23 years of follow-up. The PKD1 genotype was significantly associated with both the log of height-adjusted cyst number and volume in the linear mixed model, suggesting that the PKD1 genotype (with similar relationships for MSG groups) has a significant effect on both the cyst number and volume at a given age, but they did not significantly affect the rate of growth (although there seemed to be a positive, albeit nonsignificant association). The knowledge of the growth patterns of kidney cyst number and volume may provide additional insight in the clinical management and treatment development for patients with ADPKD.

## Disclosures

Dr. Bae is a consultant to Kadmon and Otsuka. Dr. Chapman is a Steering Committee member for Otsuka Pharmaceuticals. Dr. Harris reports grants from Otsuka Pharmaceuticals, outside the submitted work. Dr. Mrug reports grants, personal fees and nonfinancial support from Otsuka, grants, personal fees and nonfinancial support from Sanofi, personal fees from ClearView Healthcare Partners, personal fees from Decision Resources Group Consulting, personal fees from CLARION Healthcare, outside the submitted work; and serves as the PKD Foundation Scientific Advisory Committee Chair. Dr. Torres reports grants and other from Otsuka Pharmaceuticals, during the conduct of the study; grants and other from Palladio Biosciences, other from Mironid, grants and other from Sanofi Genzyme, other from Vertex, grants from Acceleron Pharma Inc., grants from Regulus Therapeutics, and grants from Palladio Biosciences, outside the submitted work. Dr. Yu reports other from Regulus Therapeutics and personal fees from Sanofi, outside the submitted work. Dr. Bennett, Dr. Landsittel, Dr. Shen, Dr. Tao, Dr. Wu, and Dr. Zhou have nothing to disclose.

## Supplemental Material

This article contains the following supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.10360818/-/DCSupplemental.

Supplemental Table 1. Characteristics of cohort compared between baseline and visits.

Supplemental Table 2. Height-adjusted total cyst number over time for all participants (A) and for participants with at least one visit in the periods 0–5, 6–10, and over 10 years after baseline (B).

Supplemental Table 3. Height-adjusted total cyst volume over time for all participants (A) and for participants with at least one visit in the periods 0–5, 6–10, and over 10 years after baseline (B).

Supplemental Table 4. Median height-adjusted total cyst number (A) and median total cyst number (B) by baseline age group and genotype.

Supplemental Table 5. Linear mixed model for repeated measures of log of height-adjusted total cyst number (A) and cyst volume (B) according to MSG.

Supplemental Table 6. Linear mixed model for repeated measures of log height-adjusted total cyst number (A) and cyst volume (B) according to PKD1 truncating or nontruncating and Irazabal class.

Supplemental Table 7. Linear mixed models with interaction by age to assess rate of change in log height-adjusted total cyst number (A) and cyst volume (B) according to MSG.

Supplemental Table 8. Linear mixed models with an interaction by age to assess rate of change in log height-adjusted total cyst number (A) and cyst volume (B) according to PKD1 truncating or nontruncating and Irazabal class.

Supplemental Figure 1. Histograms and q-q plots of height-adjusted total kidney volume (A and B), height-adjusted total cyst number (C and D) and height-adjusted total cyst volume (E and F) before and after log transformation. Histograms and q-q plots before and after log transformation are on the left and right panel, respectively. Height-adjusted total kidney volume, total cyst number, and total cyst volume that are originally right skewed become normally distributed after log transformation.

## Acknowledgments

The investigators are indebted to the radiologists, radiology technologists, imaging engineers, and study coordinators in the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study. Mr. Tiange Shi also preformed additional statistical analyses to address reviewer comments.

The CRISP study is supported by cooperative agreements from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (DK056943, DK056956, DK056957, and DK056961), and by R01 DK113111. This study was also supported in part by the NIDDK through P30 grants to the Kansas PKD Research and Translation Core Center (DK106912) and the Mayo Translational PKD Center (DK090728), by the National Center for Research Resources General Clinical Research Centers at each institution (RR000039, Emory University; RR00585, Mayo College of Medicine; RR23940, Kansas University Medical Center; RR000032, University of Alabama at Birmingham), and the National Center for Advancing Translational Sciences Clinical and Translational Science Awards at each institution (RR025008 and TR000454, Emory; RR024150 and TR000135, Mayo College of Medicine; RR033179 and TR000001, Kansas University Medical Center; RR025777, TR000165, and TR001417, University of Alabama at Birmingham; RR024153 and TR000005, University of Pittsburgh School of Medicine). D.P. Landsittel reports grants from NIDDK R01 grant to the University of Pittsburgh.

## Footnotes

Published online ahead of print. Publication date available at www.cjasn.org.

- Received October 19, 2018.
- Accepted March 22, 2019.

- Copyright © 2019 by the American Society of Nephrology